BackgroundElectric field therapies such as Tumor Treating Fields (TTFields) have emerged as a bioelectronic treatment for isocitrate dehydrogenase wild-type and IDH mutant grade 4 astrocytoma Glioblastoma (GBM). TTFields rely on alternating current (AC) electric fields (EF) leading to the disruption of dipole alignment and induced dielectrophoresis (DEP) during cytokinesis. Although TTFields have a favourable side effect profile, particularly compared to cytotoxic chemotherapy, survival benefits remain limited (~ 4.9 months) after an extensive treatment regime (20 hours/day for 18 months). The cost of the technology also limits its clinical adoption worldwide. Therefore, the discovery of new technology that can enhance both the therapeutic efficiency and efficacy of these TTFields will be of great benefit to cancer treatment and decrease healthcare costs worldwide.MethodsIn this work, we report the role of electrically conductive gold (GNPs), dielectric silica oxide (SiO2), and semiconductor zinc oxide (ZnO) nanoparticles (NPs) as transducers for enhancing EF mediated anticancer effects on patient derived GBM cells. Physicochemical properties of these NPs were analyzed using spectroscopic, electron microscopy, and light-scattering techniques.ResultsIn vitro TTFields studies indicated an enhanced reduction in the metabolic activity of patient-derived Glioma INvasive marginal (GIN 28) and Glioma contrast enhanced core (GCE 28) GBM cells in groups treated with NPs vs. control groups, irrespective of NPs dielectric properties. Our results indicate the inorganic NPs used in this work enhance the intracellular EF effects that could be due to the virtue of bipolar dielectrophoretic and electrophoretic effects.ConclusionsThis work presents preliminary evidence which could help to improve future EF applications for bioelectronic medicine. Furthermore, the merits of spherical morphology, excellent colloidal stability, and low toxicity, make these NPs ideal for future studies for elucidating the detailed mechanism and efficacy upon their delivery in GBM preclinical models.

The vagus nerve is involved in the autonomic regulation of physiological homeostasis, through vast innervation of cervical, thoracic and abdominal visceral organs. Stimulation of the vagus with bioelectronic devices represents a therapeutic opportunity for several disorders implicating the autonomic nervous system and affecting different organs. During clinical translation, vagus stimulation therapies may benefit from a precision medicine approach, in which stimulation accommodates individual variability due to nerve anatomy, nerve-electrode interface or disease state and aims at eliciting therapeutic effects in targeted organs, while minimally affecting non-targeted organs. In this review, we discuss the anatomical and physiological basis for precision neuromodulation of the vagus at the level of nerve fibers, fascicles, branches and innervated organs. We then discuss different strategies for precision vagus neuromodulation, including fascicle- or fiber-selective cervical vagus nerve stimulation, stimulation of vagal branches near the end-organs, and ultrasound stimulation of vagus terminals at the end-organs themselves. Finally, we summarize targets for vagus neuromodulation in neurological, cardiovascular and gastrointestinal disorders and suggest potential precision neuromodulation strategies that could form the basis for effective and safe therapies.

BackgroundChildren with frequently relapsing nephrotic syndrome (FRNS) and steroid resistant nephrotic syndrome (SRNS) are exposed to immunosuppressant medications with adverse side effects and variable efficacy. Transcutaneous auricular vagus nerve stimulation (taVNS) modulates the immune system via the inflammatory reflex and has become a therapy of interest for treating immune-mediated illnesses.MethodsAn open-label, pilot study of tavNS for five minutes daily for 26 weeks via a TENS 7000 unit was conducted.ResultsThree FRNS participants and 4 SRNS participants had a mean age of 9.5±4.2 years (range 4 to 17). Those with FRNS remained relapse-free during the study period; two participants continued treatment and remained in remission for 15 and 21 months, respectively. Three SRNS participants experienced a reduction in first morning UPC (mean of 42%, range 25-76%). Although UPC decreased (13.7%) in one SRNS participant with congenital nephrotic syndrome, UPC remained in nephrotic range. All but one participant (non-compliant with treatment) experienced a reduction in TNF (7.33pg/mL vs. 5.46pg/mL, p=0.03). No adverse events or side effects were reported.ConclusionstaVNS was associated with clinical remission in FRNS and moderately reduced proteinuria in non-congenital SRNS. Further study of taVNS as a treatment for nephrotic syndrome in children is warranted.ClinicalTrials.gov Identifier: NCT04169776, Registered November 20, 2019, https://clinicaltrials.gov/ct2/show/NCT04169776.

BackgroundA detailed sensorimotor evaluation is essential in planning effective, individualized therapy post-stroke. Robotic kinematic assay may offer better accuracy and resolution to understand stroke recovery. Here we investigate the added value of distal wrist measurement to a proximal robotic kinematic assay to improve its correlation with clinical upper extremity measures in chronic stroke. Secondly, we compare linear and nonlinear regression models.MethodsData was sourced from a multicenter randomized controlled trial conducted from 2012 to 2016, investigating the combined effect of robotic therapy and transcranial direct current stimulation (tDCS). 24 kinematic metrics were derived from 4 shoulder-elbow tasks and 35 metrics from 3 wrist and forearm evaluation tasks. A correlation-based feature selection was performed, keeping only features substantially correlated with the target attribute (R > 0.5.) Nonlinear models took the form of a multilayer perceptron neural network: one hidden layer and one linear output.ResultsShoulder-elbow metrics showed a significant correlation with the Fugl Meyer Assessment (upper extremity, FMA-UE), with a R = 0.82 (P < 0.001) for the linear model and R = 0.88 (P < 0.001) for the nonlinear model. Similarly, a high correlation was found for wrist kinematics and the FMA-UE (R = 0.91 (P < 0.001) and R = 0.92 (P < 0.001) for the linear and nonlinear model respectively). The combined analysis produced a correlation of R = 0.91 (P < 0.001) for the linear model and R = 0.91 (P < 0.001) for the nonlinear model.ConclusionsDistal wrist kinematics were highly correlated to clinical outcomes, warranting future investigation to explore our nonlinear wrist model with acute or subacute stroke populations.Trial registrationhttp://www.clinicaltrials.gov. Actual study start date September 2012. First registered on 15 November 2012. Retrospectively registered. Unique identifiers: NCT01726673 and NCT03562663.

Conventional neurostimulation systems for preclinical research can be bulky and invasive due to the need for batteries or wired interfaces. Emerging as a new neural interface technique, ultrasound-powered piezoelectric neural stimulators work by converting ultrasound energy to electrical charge for neural stimulation. In addition to the benefits of wireless powering and miniaturization leading to less traumatic surgery, piezoelectric neural stimulators can also exhibit prolonged operational lifetimes for a long-term stable neural interface, and show promise for clinical translation. As one of first steps to demonstrate the value of ultrasound-powered piezoelectric neural interface, Li et al. developed a piezoelectric stimulator to activate spinal cord neural circuits for locomotion restoration in a rat model with spinal cord injury (SCI) and compared its efficacy with conventional electrical stimulation (ES). From the point of view of materials science, neural engineering and microelectronics, we provide our commentary on the article, highlighting its importance and discussing the issues that remain to be addressed in future studies in the emerging field of ultrasound powered piezoelectric neurostimulation devices.

BackgroundInflammation and swelling of the sinus and nasal mucosa are commonly caused by viral infection, bacterial infection, or exposure to allergens and irritants. Sinonasal inflammation can cause symptoms of nasal congestion, facial pressure, and rhinogenic facial pain or “sinus pain”. A previous randomized controlled study demonstrated that acute treatment with non-invasive periorbital microcurrent stimulation resulted in a rapid and clinically meaningful reduction in self-report of sinus pain that significantly outperformed sham control treatment. Here, we assessed the acute durability of microcurrent pain relief and longitudinal effects of 4 weeks of daily microcurrent treatment in patients presenting with sinus pain.MethodsThirty subjects with moderate facial pain (numeric rating scale ≥5) attributed to self-reported sinonasal disease were enrolled in a single-arm, prospective interventional study. At enrollment, subjects were given a microcurrent treatment device and written instructions and self-administered the device to the bilateral periorbital regions for 5 mins. Subjects were instructed to treat themselves at home once daily and up to four times daily as needed for 4 weeks. Pain was measured both acutely and weekly during the 4 weeks of treatment using the numeric rating scale. Congestion and medication use data were collected weekly using the Congestion Quantifier 7 (CQ7) and medication diary, respectively.ResultsThirty patients were enrolled and completed the study. Microcurrent therapy rapidly reduced post-treatment numeric rating scale for pain by − 1.2 at 10 mins (p = 0.0076), − 1.6 at 1 hr (p = 0.0007), − 1.9 at 2 hrs (p < 0.0001), − 2.1 at 4 hrs (p < 0.0001), and − 2.1 at 6 hrs (p < 0.0001). With daily microcurrent treatment, numeric rating scale for pain was reduced over 4 weeks by − 1.3 (− 20.1%) after 1 week (p = 0.0018), − 2.1 (− 32.1%) after 2 weeks (p < 0.0001), − 2.4 (− 36.6%) after 3 weeks (p < 0.0001) and − 2.9 (− 43.3%) after 4 weeks (p < 0.0001). For subjects who enrolled with moderate or worse congestion, mean congestion scores (CQ7) were reduced by − 4.2 (− 22.0%) after 1 week (p < 0.0001), − 5.8 (− 33.0%) after 2 weeks (p < 0.0001), − 7.2 (− 37.4%) after 3 weeks (p < 0.0001) and − 8.6 (− 44.3%) after 4 weeks (p < 0.0001) of microcurrent treatment.ConclusionSelf-administered periorbital microcurrent treatment given at home was efficacious in significantly reducing moderate sinus pain for up to 6 hrs and significantly reducing moderate pain and congestion over 4 weeks of daily use. Microcurrent therapy was found to be safe with only minor side effects that resolved without intervention.Trial registrationClinicalTrials.gov, NCT03888274. Registered 25 March 2019. Retroactively registered, https://clinicaltrials.gov/ct2/show/NCT03888274.

BackgroundGlucose is a crucial energy source. In humans, it is the primary sugar for high energy demanding cells in brain, muscle and peripheral neurons. Deviations of blood glucose levels from normal levels for an extended period of time is dangerous or even fatal, so regulation of blood glucose levels is a biological imperative. The vagus nerve, comprised of sensory and motor fibres, provides a major anatomical substrate for regulating metabolism. While prior studies have implicated the vagus nerve in the neurometabolic interface, its specific role in either the afferent or efferent arc of this reflex remains elusive.MethodsHere we use recently developed methods to isolate and decode specific neural signals acquired from the surface of the vagus nerve in BALB/c wild type mice to identify those that respond robustly to hypoglycemia. We also attempted to decode neural signals related to hyperglycemia. In addition to wild type mice, we analyzed the responses to acute hypo- and hyperglycemia in transient receptor potential cation channel subfamily V member 1 (TRPV1) cell depleted mice. The decoding algorithm uses neural signals as input and reconstructs blood glucose levels.ResultsOur algorithm was able to reconstruct the blood glucose levels with high accuracy (median error 18.6 mg/dl). Hyperglycemia did not induce robust vagus nerve responses, and deletion of TRPV1 nociceptors attenuated the hypoglycemia-dependent vagus nerve signals.ConclusionThese results provide insight to the sensory vagal signaling that encodes hypoglycemic states and suggest a method to measure blood glucose levels by decoding nerve signals.Trial registrationNot applicable.

The Cleveland Neural Engineering Workshop (NEW) is a biennial meeting started in 2011 as an “unconference” to bring together leaders in the neural engineering and related fields. Since the first iteration of the meeting, NEW has evolved from “just getting together” to a more important purpose of creating, reviewing, and promoting a uniform strategic roadmap for the field. The purpose of this short report, as well as the companion 2015 and 2017 reports, is to provide a historical record of this meeting and the evolution of the roadmap. These reports more importantly establish a baseline for the next meeting to be held in June, 2019. The second Neural Engineering Workshop (NEW) was held in June 2013. The two-day workshop was hosted by the Cleveland Advanced Platform for Technology National Veterans Affairs Center, the Functional Electrical Stimulation National Veterans Affairs Center, and the Case Western Reserve University in Cleveland, Ohio. Participants identified seven areas of future focus in the field of neural engineering: active communications with users, advocacy (regulatory), network building (clinical practice), case studies (clinical and technical), early industrial feedback, value chain resources, engagement, and advocacy (funding). This proceedings document summarizes the meeting outcome.

BackgroundNeurodegenerative diseases are devastating diagnoses. Examining local electric fields in response to neural activity in real time could shed light on understanding the origins of these diseases. To date, there has not been found a way to directly map these fields without interfering with the electric circuitry of the brain. This theoretical study is focused on a nanotechnology concept to overcome the challenge of brain electric field mapping in real time. The paper shows that coupling the magnetoelectric effect of multiferroic nanoparticles, known as magnetoelectric nanoparticles (MENs), with the ultra-fast and high-sensitivity imaging capability of the recently emerged magnetic particle imaging (MPI) can enable wirelessly conducted electric-field mapping with specifications to meet the requirements for monitoring neural activity in real time.MethodsThe MPI signal is numerically simulated on a realistic human brain template obtained from BrainWeb, while brain segmentation was performed with BrainSuite software. The finite element mesh is generated with Computer Geometry Algorithm Library. The effect of MENs is modeled through local point magnetization changes according to the magnetoelectric effect.ResultsIt is shown that, unlike traditional magnetic nanoparticles, MENs, when coupled with MPI, provide information containing electric field’s spatial and temporal patterns due to local neural activity with signal sensitivities adequate for detection of minute changes at the sub-cellular level corresponding to early stage disease processes.ConclusionsLike no other nanoparticles known to date, MENs coupled with MPI can be used for mapping electric field activity of the brain at the sub-neuronal level in real time. The potential applications span from prevention and treatment of neurodegenerative diseases to paving the way to fundamental understanding and reverse engineering the brain.

BackgroundUnderstanding the long-term behavior of intracortically-recorded signals is essential for improving the performance of Brain Computer Interfaces. However, few studies have systematically investigated chronic neural recordings from an implanted microelectrode array in the human brain.MethodsIn this study, we show the applicability of wavelet decomposition method to extract and demonstrate the utility of long-term stable features in neural signals obtained from a microelectrode array implanted in the motor cortex of a human with tetraplegia. Wavelet decomposition was applied to the raw voltage data to generate mean wavelet power (MWP) features, which were further divided into three sub-frequency bands, low-frequency MWP (lf-MWP, 0–234 Hz), mid-frequency MWP (mf-MWP, 234 Hz–3.75 kHz) and high-frequency MWP (hf-MWP, >3.75 kHz). We analyzed these features using data collected from two experiments that were repeated over the course of about 3 years and compared their signal stability and decoding performance with the more standard threshold crossings, local field potentials (LFP), multi-unit activity (MUA) features obtained from the raw voltage recordings.ResultsAll neural features could stably track neural information for over 3 years post-implantation and were less prone to signal degradation compared to threshold crossings. Furthermore, when used as an input to support vector machine based decoding algorithms, the mf-MWP and MUA demonstrated significantly better performance, respectively, in classifying imagined motor tasks than using the lf-MWP, hf-MWP, LFP, or threshold crossings.ConclusionsOur results suggest that using MWP features in the appropriate frequency bands can provide an effective neural feature for brain computer interface intended for chronic applications.Trial registrationThis study was approved by the U.S. Food and Drug Administration (Investigational Device Exemption) and the Ohio State University Medical Center Institutional Review Board (Columbus, Ohio). The study conformed to institutional requirements for the conduct of human subjects and was filed on ClinicalTrials.gov (Identifier NCT01997125).